import streamlit as st import PyPDF2 import base64 # Function to display PDF def display_pdf(file_path): try: with open(file_path, 'rb') as file: base64_pdf = base64.b64encode(file.read()).decode('utf-8') pdf_display = f'' st.markdown(pdf_display, unsafe_allow_html=True) except Exception as e: st.error(f"Error reading PDF file: {e}") # Function to display resume contents def display_resume(): st.title("Ruthvik Kilaru") st.sidebar.header("Profile Summary") st.sidebar.header("Functional Skills") st.sidebar.header("Technical Skills") st.sidebar.header("Work Experience") st.sidebar.header("Education") st.sidebar.header("Research and Publications") st.sidebar.header("Certifications") st.header("Profile Summary") st.write(""" - Detail-oriented professional with over 4 years of extensive experience in analyzing complex datasets to drive informed decision-making. - Proficient in ETL processes, data warehousing, big data technologies, Hadoop, Spark, and Kafka, Python, R, SQL, machine learning frameworks such as TensorFlow and scikit-learn, statistical analysis, data visualization, and business intelligence tools. - Experienced in developing and deploying data-driven solutions to solve complex business problems. - Skilled in data preprocessing, feature engineering, and model optimization, with a focus on achieving high accuracy and interpretability. - Experienced in natural language processing, computer vision, and time series analysis. - Expert in transforming raw data into actionable insights, enabling businesses to optimize strategies and improve operational efficiency. - Adept at communicating findings to stakeholders through clear, concise reports and dashboards. Passionate about leveraging data to solve problems and support strategic initiatives. """) st.header("Functional Skills") st.write(""" - Data Analysis - Data Cleaning - Feature Engineering - Data Visualization - Data Mining - Data Preprocessing - SQL - Business Intelligence (BI) - Data Integration - Statistical Analysis - Data Reporting - Predictive Modeling - Data Preprocessing - Machine Learning - Model Evaluation """) st.header("Technical Skills") st.write(""" - Programming Languages: Python, R, C, C++, HTML, CSS - Big Data & Machine Learning: PowerBI, Spark, Kafka, VectorDB, SQL(t-SQL, p-SQL) - Data Science and Miscellaneous Technologies: A/B testing, Jira, Shell scripting, ETL, Data science pipelines based on CI/CD, PowerBI(PQ, DAX, Slicers), Snowflake, NLP, GANs, LLMs, APIs(REST), Excel(Power Pivot, VBA, Macros), AWS(EC2, Kinesis streams, S3 buckets, Redshift), Google Analytics(BigQuery) & Ads, Langchain, Github, Docker & Kubernetes """) st.header("Work Experience") st.subheader("Illinois Institute of Technology, Chicago, IL | Research & Teaching Assistant | Jan 2023 – Till Date") st.write(""" - Directing joint research on how student behavior affects academic performance. - Utilizing advanced methods for person detection, emotion recognition, and posture tracking through algorithms such as Yolo, HaarCascade, PoseNet, Openpose, and AlphaPose. - Prototyping an Educational Advising Chatbot using RAG architecture with Langchain on AWS, showcasing integration of advanced AI frameworks and cloud technologies. - Organizing and preparing data for RAG-based chatbot by employing web scraping tools like BeautifulSoup and Unstructured.io, effectively gathering and structuring web data. - Improving chatbot’s performance by refining and prompt-tuning it with synthetic data generated through LLMs and CI workflows, applying Evol Instruct and Contrastive Learning methods to enhance metrics. - Conducting instructor-led recitations, grading assignments, and addressing over 250 student queries through 30+ interactive sessions, increasing engagement. - Developing a Python grading algorithm with Professor Yong Zheng, automating processes and saving 40 TA hours. """) st.subheader("Genesis Solutions, Hyderabad, India | Data Scientist | Jan 2021 – May 2022") st.write(""" - Leveraged advanced regression techniques, including polynomial regression and ridge regression, to achieve a remarkably low Root Mean Squared Error (RMSE) of 5.27 in Stock Price Prediction Analysis. - Demonstrated proficiency in accurately forecasting stock prices, as evidenced by model's performance. - Achieved an R-squared value of 0.87, indicating model's robustness by explaining 87% of variability in stock prices. - Implemented a sophisticated text detection system using OpenCV for image processing and PyTesseract for Optical Character Recognition (OCR). - Attained impressive Precision (0.92), Recall (0.89), and F1-score (0.90) in text region identification within images. - Optimized algorithm for efficiency, enabling it to process images at a speed of 15 frames per second, making it suitable for real-time applications. """) st.subheader("Vedanta Resources Pvt Ltd, Orissa, India | Data Engineer | Jul 2019 – Nov 2021") st.write(""" - Worked on real-time data in production department to make necessary technical improvements in that area. - Developed and deployed Kafka and Spark-based data pipeline(Debezium connectors, Apache hudi, STARGAZE, Hive for metadata), enhancing data throughput by 15% and reducing waste by 10% via real-time analytics of 1+ million daily data points. - Enhanced SQL database for supply chain efficiency, halving query times and cutting inventory costs by 5% through improved Forecasting. """) st.header("Education") st.write(""" - Masters in Information Technology (Data Science) from Illinois Institute of Technology, College of Computing – 2024 - Bachelor of Technology from National Institute of Technology, Jamshedpur, India – 2019 """) st.header("Research and Publications") st.write(""" - International Conference on Recent Trends in Computer Science and Technology (ICRTCST) – IEEE 2021 - Prediction of Maize Leaf Disease Using ML Models - Implemented Support Vector Machine (SVM) techniques that demonstrated superior accuracy in detecting maize diseases, achieving a high accuracy rate of 95.6%. This highlights ability to effectively apply machine learning algorithms to solve real-world agricultural problems. - Integrating Discrete Wavelet Transform (DWT) and YOLOv5 architecture for feature extraction and disease classification, my research contributed to a predictive model that increased precision of crop yield forecasts due to early disease detection, reflected in a sensitivity improvement of up to 92.3%. """) st.header("Certifications") st.write(""" - Building Transformer-Based Natural Language Processing Applications from NVIDIA – Feb 2024 - Generative AI with Diffusion Models from NVIDIA – Feb 2024 - Building LLM-Powered Applications from W&B – Jan 2024 - GCP - Google Cloud Professional Data Engineer from Udemy – Jan 2024 - Large Language Models: Application through Production from Databricks – Dec 2023 - Deep Learning- PadhAI from One Fourth Labs – Sep 2021 - Machine Learning from Stanford Online – Aug 2021 - Foundations in Data Science- PadhAI from One Fourth Labs – May 2021 """) st.sidebar.download_button( label="Download Resume", data=open("path/to/your/resume.pdf", "rb").read(), file_name="Ruthvik_Kilaru_Resume.pdf", mime="application/pdf", ) if __name__ == "__main__": display_resume()